Xueyuan Zhou, Mikhail Belkin, Nathan Srebro
Abstract
Ranking is one of the key problems in information retrieval. Recently, there has been significant interest in a class of ranking algorithms based on the assumption that data is sampled from a low dimensional manifold embedded in a higher dimensional Euclidean space.
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Ranking is one of the key problems in information retrieval. Recently, there has been significant interest in a class of ranking algorithms based on the assumption that data is sampled from a low dimensional manifold embedded in a higher dimensional Euclidean space.
Key concepts: Euclidean space, Ranking (information retrieval), Iterated function, Computer science, Graph, Manifold (fluid mechanics), Nonlinear dimensionality reduction, Laplace operator